1. Field of the Invention
The present invention pertains to distributed data storage; more particularly, the present invention describes a distributed, highly scalable, wide area peer-to-peer network data storage system and method.
2. Background of the Invention
The problem of data storage in a computer network appeared immediately after computers started to be connected to one another. The data storage problem has typically been solved by providing one of the computers with the necessary service, i.e., by organization of the file server. When one of the computers has an organized file server, the other computers in the network have software installed that provides the work using the files saved on the correspondent servers. For example, the data storage files could be copied locally; or, more conveniently, access to the network data storage files could be imitated if the data storage files are saved on a virtual hard disk. DOS software usable on IBM personal computers was developed in such a way. For IBM computers, the client software that was to be installed would provide a user with a so-called network drive, if the connection to the network and to the corresponding file server was successful. Physically, network data storage files were located on the remote file server, but for the programs running on the client computer, they appeared to the user as if they were on local servers (Beheler 1987).
The foregoing system for providing access to the stored data implies a separated file server and client computer server access model. This means that it appears to the user that there are separated roles in the network—the roles of client and server (Crowley 1997).
While workable, the data storage system described above has many disadvantages. For example, every data storage file being accessed “pseudo-locally” actually resides on a remote server. In case somebody tries to provide the stored file with shared access, (i.e., several clients have a chance to see the same file) the programs running on the client computer (not knowing about the data storage scheme) can start writing in the same file. Writing in the same file can lead to content errors.
The next problem is that the data storage file itself, being situated on only one server (and more importantly, on one hard disk), cannot be accessed in case of failures in the data storage file server equipment, network problems, or server software failures (i.e., many “failure points” appear, which means “no access” to the data). Such inability to access data even appears in case of workable server equipment when a computer user must reboot an operating system. When rebooting a data storage file, access service becomes unavailable for the clients, which means a break in use again.
One of the solutions to the problem of accessibility to data storage files is to use the clusterization principle. The best-known data storage solution was implemented in the platform developed by Digital Equipment (DEC) company. The clusterization principle was based on the creation of a special hard disk array that could hold data and be connected to several processor units (computers) (Davis). In clusterization, sharing access to a data storage file was done by using special equipment, and not only by the separated computer.
This use of special equipment enabled the full interchangeability of all the processor units. The equipment that managed the clusterization support was of minor complexity, and therefore had higher reliability when compared with the separate computer. Particularly, it meant the absence of the clusterization process support software and the associated mistakes. Nevertheless, the special client software was to be installed into the operating systems of the client computers. Clusterization solved the problem of computers' interchangeability and the computer's independence of the services to which any client computer had access. Nevertheless, the equipment failure of clusterization hardware led to the problem of service unavailability.
More problems appear if the server and its data storage services are separated by distance and are connected via the internet. The typical example is a single server with data storage files, which gains access to the data storage services via special network protocols, such as the World Wide Web service protocol called http (Network Working Group). Such network protocols are specifically used in a distributed client-server network that is not as close as the local network described above.
Another Internet service feature is the necessity to service a great number of client computers trying to access necessary data. The number of client computers can be so large that the server itself can become inaccessible when trying to respond to the client computers' requests for data (due to the insufficient network throughput capacity or server's inability to answer every request). That is why it is clear that the approach with one stand-alone server (and even a group of servers located in one place) and client computers connected via the Internet leads to failures caused by the distance between the server and the client.
Therefore, the optimal situation for a client computer is a service or server located in the network closest to the client computer. Because of the large number of client computers, it is clear that it is necessary to have a distributed set of similar servers over the Internet and to choose the closest servers among them.
Such a solution assures a symmetry of service for each client computer, and therefore the same data accessibility for all servers, provided that appropriate connections to the client computers exist. The easiest way to solve this problem is the simple doubling of the data on each server and then providing fully symmetrical service, independent of the client computer and the location it requests to obtain the service (U.S. Pat. No. 6,092,178). Such a decision at the same time presents many additional problems, such as data synchronization.
To provide such a service, dedicated distributed data storage was developed that made it possible to access data storage files. In a distributed data storage system, the distribution of the service means actually running the server processes of the operational systems at the corresponding network unit (at the server) (Davis and Pfister 1998). Such an approach helps to minimize access time and, at the same time, the problem of channel throughput between servers and the client computer.
Simultaneously, a distributed data storage system helps resolve the situation where computational power for the only computer is insufficient to perform all requests because a greater number of computers try to get service at the same time. Even in case of non-parallel request servicing, a distributed data storage system reduces the load on any server because the requests are distributed among the servers available. In addition, the level of resistance to failure grows. If the server becomes unavailable, the client computer can switch to another server and get the same service (determined by the symmetry range of the system servers) (Pfister 1998).
A distributed service must have a distributed data storage system, as the range of client services is usually based on this data.
To implement such distributed storage of data, it is necessary to develop data distribution and data storage algorithms. These algorithms must provide optimal data storage with respect to contents and resource utilization so that they provide the same contents on different servers based on the level of server symmetry.
Presently, these solutions typically use very complicated algorithms to access stored data. Data full duplex (mirroring) is used when every unit of the network has the full copy of the stored data files. For example, Internet FTP server mirror systems use this approach (U.S. Pat. Nos. 5,835,911, 5,434,994, 5,155,847, and 5,742,792).
A general network file system (for example, UNIX NFS system developed by Sun Microsystems, Inc. (Chet 1994) usually means the separated server and the client computer know what server to be connected to. Such general network file systems are usually intended for use with a minimum of separated servers.
Network distributed file systems are arranged in a more complicated way. They generally allow working in a shared uniform namespace whether a specific file server is accessible or not. Namespace is a collection of unique names, where name is an arbitrary identifier, usually an integer or a character string. Usually the term “name” is applied to such objects as files, directories, devices, computers, etc. For example, Open Software Foundation DFS (Distributed File System) is of such structure (Kumar 1991, Lebovitz 1992, Distributed File System, Rosenberry 1992, and Pfister 1998). Its namespace hierarchy stems from a shared point, i.e., root, of a file system. Nevertheless, every DFS name corresponds to a specific file server. Its loss entails disappearance of access to certain files. As this takes place, files get split apart. To make them more accessible, a program finds the way inside the namespace and recognizes the server wanted. Thus, there exists a potential interchangeability of files, but, even if properly organized, fault-tolerance level of the system is not higher than usual.
Another approach is the hierarchical system of file naming, combined with local data caching on a client server. Transarc Corporation (now IBM Transarc Labs) AFS (Campbell 1997) and Coda (Braam 1998 and Satyanarayanan 1989) systems use a hierarchical file naming system. To optimize data access, these systems cache data on the client side using cache to reduce the number of requests to the server. The AFS server broadcasts every request on the file (even on the one situated in cache) to the server data storage file, and only after getting the information that the data storage file has not changed since being copied into a local cache, the system provides access to it. If there is no connection with the data storage file server, the AFS system doesn't usually make it possible to use the data storage file. This can provide a Coda system by taking into account the fact that the files usually don't change and access is not waiting for connection with the file server.
Such an approach is more resistant to failures compared with several dedicated servers, which must be online all the time. Nevertheless, such an approach can lead to problems if several clients working with the same file simultaneously make concurrent changes that can lead to incorrect work in the future. Both approaches imply that the file is saved in cache, which means that there are many copies of the different file modifications in the network. The presence of many copies of different file modifications complicates file system serviceability control, i.e., data coherence. Moreover, these approaches imply that the access to the files that are not in cache will be possible only after their full extract to this cache. Access to files not in cache means that the support of the server system where different data is stored on different servers can lead to access problems in the case where connection to the server is lost.
The other method of distributed file access is the distribution not of the file but of the determination of distributed blocks' storage upon which the file system itself is built. The main problem with such a method is the necessity to place constant locks on the blocks where the internal (usually directory) information is stored due to concurrent access to them.
Another method is to use the approach similar to the one used in a RAID redundant data storage system. The RAID redundant data storage system makes it possible, with little redundancy, to access data even when one of the servers or hard disks becomes inaccessible. This particular method is called Level 5 RAID (Pfister 1998) and is used widely to increase the reliability of a disk array. The Level 5 RAID method was used for the so-called “serverless file system” built at the University of California at Berkeley (Anderson 1995), where the system did not have just one separated file system; rather, it had a group of them. Nevertheless, such realization isn't very flexible and is used for tightly coupled networks. Besides, the system allowed no use of servers with unequal efficiency and connection quality, as data accessibility depended on access to all of the servers, whether they were overloaded or not (with the exception of one with data parity recording). It simply is not suitable for data storage over the Internet.
What is needed is a system and method for distributed network data storage which minimizes content errors, access time and system failures. Such a system and method should maximize reliability, accessibility, and uniformity of data stored within the system. Additionally, there is a need for a method which provides a high degree of data coherence and synchronization, data storage flexibility, and maximum channel throughput and serviceability.